Super-Duper Ising Machine featured in Physics!

New hardware for solving NP-complete problems is of paramount importance in the modern theory of complexity and computation. In the new era of machine learning and quantum computing, many groups are working for realizing “annealing devices.” Ising machines are a special class that finds the minima of spin-glass Hamiltonians, as Sherrington-Kirkpatrick and Mattis models. Our recent work on a new simple and scalable Ising machine [Phys.Rev.Lett. 122, 213902(2019) and arXiv:1905.11548] has been featured in Physics.

Photonic Ising Machines Go Big: A new optical processor for solving hard optimization problems breaks previous size records and is based on a highly scalable technology”

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Super-Duper Ising Machine by a Single SLM

Quantum and classical physics can be used for mathematical computations that are hard to tackle by conventional electronics. Very recently, optical Ising machines have been demonstrated for computing the minima of spin Hamiltonians, paving the way to new ultra-fast hardware for machine learning. However, the proposed systems are either tricky to scale or involve a limited number of spins. We design and experimentally demonstrate a large-scale optical Ising machine based on a simple setup with a spatial light modulator. By encoding the spin variables in a binary phase modulation of the field, we show that light propagation can be tailored to minimize an Ising Hamiltonian with spin couplings set by input amplitude modulation and a feedback scheme. We realize configurations with thousands of spins that settle in the ground state in a low-temperature ferromagnetic-like phase with all-to-all and tunable pairwise interactions. Our results open the route to classical and quantum photonic Ising machines that exploit light spatial degrees of freedom for parallel processing of a vast number of spins with programmable couplings.

D. Pierangeli, G. Marcucci, C. Conti in ArXiv:1905.11548 and Phys. Rev. Lett. 122, 213902 (2019)

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Quantum Gates by TensorFlow and Reservoir Computing

Novel machine learning computational tools open new perspectives for quantum information systems. Here we adopt the open-source programming library TensorFlowTM to design multi-level quantum gates including a computing reservoir represented by a random unitary matrix. In optics, the reservoir is a disordered medium or a multimodal fiber. We show that trainable operators at the input and the readout enable to realize multi-level gates. We study single and qudit gates, including the
scaling properties of the algorithms with the size of the reservoir.

Quantum Reservoir Computing

G. Marcucci et al. in arXiv:1905.05264

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Flexible Organometal Random Lasers

Disorder is emerging as a strategy for fabricating random laser sources with very promising materials, like perovskites, for which standard laser cavities are not effective, or too expensive. We need however different fabrication protocols and technologies for reducing the laser threshold and controlling its emission. Here we demonstrate an effectively solvent-engineered method for high-quality perovskite thin films on the flexible polyimide substrate. The fractal perovskite thin films exhibit excellent optical properties at room temperature and easily achieve lasing action without any laser cavity above room temperature with a low pumping threshold. The lasing action is also observed in curved perovskite thin films on the flexible substrates. The lasing threshold can be further reduced by increasing the local curvature, which modifies the scattering strengths of the bent thin film. We also show that the curved perovskite lasers are extremely robust with respect to repeated deformations. Because of the low spatial coherence, these curved random laser devices are efficient and durable speckle-free light sources for applications in spectroscopy, bio-imaging, and illumination.

Wang et al. in ACS Nano (2019)


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Nonlinear localized waves in curved geometry
Lasing in curved geometry

Graphene oxide photonics

The successful exfoliation of graphite initiated new science in any research field and is employing a huge number of scientists in the world investigating chemical, structural, mechanical and optoelectrical; properties of the atomic-thick sheets of graphene and graphene oxide. Similarly to other carbon-based materials, graphene family have shown exceptional optical responses; and nowadays it is engineered to produce efficient photonic components. In this review we aim to summarize the main results in nonlinear optical response and fluorescence of graphene oxide; moreover, its laser printing is reviewed as a novel promising lithographic technique.

Neda Ghofraniha and Claudio Conti in Journal of Optics


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